Then I excluded history subreddits and looked at the probability that a Reddit thread mentions Nazis or Hitler at least once. Unsuprisigly, the probability of a Nazi refrence increases as the threads get bigger. Nevertheless, I didn’t expect that the probability would be over 70% for a thread with more than 1,000 comments.

The blogger expressly states that his data mining doesn't attempt to show that:

Let me start this post by noting that I will not attempt to test Godwin’s Law,

and:

The next step would be to implement sophisticated text mining techniques to identify comments which use Nazi analogies in a way as described by Godwin. Unfortunately due to time constraints and the complexity of this problem, I was not able to try for this blog post.

There's not enough context in his data for him to determine that. Since history is the sub with the highest amounts of matches, it might be that people are using the words in the normal context of the words. It might just show that the history and political subs have a lot of posts where the word is appropriately used in context.

I agree that it's doubtful and that this is some evidence for Godwin's Law, but it's not necessarily causal based on his methods at this point.

It's an interesting observation, but honestly Reddit literally went to wolves looong ago. Unless you stick to really niche subs the rest is just bad. Can't even go on r/all without seeing literally hundreds of post from that dumb sub on Donald Trump.